RT info:eu-repo/semantics/article
T1 Blending Extensibility and Performance in Dense and Sparse Parallel Data Management
A1 Fresno, Javier
A1 Gonzalez-Escribano, Arturo
A1 Llanos Ferraris, Diego Rafael
K1 Informática
K1 Data partition
K1 Mapping techniques
K1 sparse structures
K1 Parallel libraries
K1 1203 Ciencia de Los Ordenadores
K1 3304 Tecnología de Los Ordenadores
AB Dealing with both dense and sparse data in parallel environments usually leads to two different approaches: To rely on a monolithic, hard-to-modify parallel library, or to code all data management details by hand. In this paper we propose a third approach, that delivers good performance while the underlying library structure remains modular and extensible. Our solution integrates dense and sparse data management using a common interface, that also decouples data representation, partitioning, and layout from the algorithmic and parallel strategy decisions of the programmer. Our experimental results in different parallel environments show that this new approach combines the flexibility obtained when the programmer handles all the details with a performance comparable to the use of a state-of-the-art, sparse matrix parallel library.
PB IEEE
SN 1045-9219
YR 2014
FD 2014
LK https://uvadoc.uva.es/handle/10324/70431
UL https://uvadoc.uva.es/handle/10324/70431
LA eng
NO IEEE Transactions on Parallel and Distributed Systems, Vol. 25, no. 10, October 2014, pages 2509-2519, ISSN 1045-9219
NO Producción Científica
DS UVaDOC
RD 06-oct-2024